Improved Target Detection in Spiky Sea Clutter using Sparse Signal Separation

Sparse signal separation is a technique that has demonstrated good performance for maritime target detection where the clutter is dynamic and non-homogeneous. Morphological component analysis (MCA) is a powerful separation algorithm, but requires careful selection of the penalty parameter to work effectively. In this paper, new methods of determining the penalty parameter are proposed and evaluated. Additional processing steps are also combined with the MCA output to improve the overall detection performance in spiky sea clutter. The new algorithms are then demonstrated against a number of traditional coherent detection schemes and compared using a Monte-Carlo simulation with simulated sea clutter.